Today, HR leaders are working in an increasingly competitive environment and face the challenge of sourcing talented job candidates with various skill sets on a global level. Fortunately, talent acquisition strategies have come a long way with the rise of artificial intelligence (AI) and other data-driven automation technologies for communicating with potential new hires and determining if they will find success within an organization. However, according to CEB only 5 percent of HR executives feel they are effective in using talent analytics due to inaccurate or duplicate data and a lack of understanding of analytics. The statistic is staggering, as data analytics can mean the difference between hiring managers making a gut decision versus a fact-driven decision.

For example, at the beginning of the hiring funnel, organizations such as Unilever and Walmart are using AI to pre-qualify candidates based on their resumes and other digital responses. They then connect them with HR professionals based on scoring and keyword categorizations. Instead of scanning candidates’ resumes for specific words, AI software uses algorithms to analyze large data sets and match, score and rank job candidates.

Additionally, AI is helping determine specific skill sets that are important to an organization as well as a predicted view into how an applicant will perform once they join a company. By constructing "identity profiles" for candidates, AI can help predict if an individual will be a good match for their position and within the company’s culture. This is critical, as 27 percent of employers said a bad hire has cost them more than $50,000, according to a CareerBuilder survey.

Other companies are using a CRM-like approach to seek out candidates and nurture them until a good fit for a position exists. This can help foster relationships between an employer and job seeker until a job opening arises.

Both AI and CRM approaches illustrate that the new world of recruiting demands accurate data regarding both candidates and open positions in order to create a good match in an efficient manner. While a candidate might apply for multiple positions, the HR team can leverage data-driven solutions to cleanse, consolidate, interpret, analyze, and assess key information into a single view and ensure a unified engagement approach based on scoring and readiness rankings for each possible role.

The common denominator for all HR emerging technologies is consistent, clean data and its availability in real time. When recruiters are examining both structured (online job application) and unstructured data (LinkedIn profile, Twitter, published articles), they need to assimilate that information into a population of potential candidates and guarantee they are only reviewing each candidate once. The accuracy of data is important for ensuring that various sources about one candidate are associated with that individual. For example, data referring to an applicant applying as James Jones, who is also known as Jim Jones, should be linked to the same job candidate.

Clean data drives better decision making and can help improve recruiting metrics, but in order for organizations to make the most of this data, various HR technologies and recruiting systems need to be connected and rigor applied to data business processes. Also, data from each technology should be accessible in one central location with a single view. Otherwise, without this visibility across platforms companies could be missing out on qualified candidates and wasting millions in lost time and resources.

Artificial intelligence, and other emerging technologies, can offer important insight into success of a particular job candidate and their potential rate of success with an organization. With insights based on real time data, HR leaders will become better equipped to make informed recruiting decisions.